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    The vertical aerosol type distribution above Israel – 2 years of lidar observations at the coastal city of Haifa
    (Katlenburg-Lindau : EGU, 2022) Heese, Birgit; Floutsi, Athena Augusta; Baars, Holger; Althausen, Dietrich; Hofer, Julian; Herzog, Alina; Mewes, Silke; Radenz, Martin; Schechner, Yoav Y.
    For the first time, vertically resolved long-term lidar measurements of the aerosol distribution were conducted in Haifa, Israel. The measurements were performed by a PollyXT multi-wavelength Raman and polarization lidar. The lidar was measuring continuously over a 2-year period from March 2017 to May 2019. The resulting data set is a series of manually evaluated lidar optical property profiles. To identify the aerosol types in the observed layers, a novel aerosol typing method that was developed at TROPOS is used. This method applies optimal estimation to a combination of lidar-derived intensive aerosol properties to determine the statistically most-likely contribution per aerosol component in terms of relative volume. A case study that shows several elevated aerosol layers illustrates this method and shows, for example, that coarse dust particles are observed up to 5ĝ€¯km height over Israel. From the whole data set, the seasonal distribution of the observed aerosol components over Israel is derived. Throughout all seasons, coarse spherical particles like sea salt and hygroscopically grown continental aerosol were observed. These particles originate from continental Europe and were transported over the Mediterranean Sea. Sea-salt particles were observed frequently due to the coastal site of Haifa. The highest contributions of coarse spherical particles are present in summer, autumn, and winter. During spring, mostly coarse non-spherical particles that are attributed to desert dust were observed. This is consistent with the distinct dust season in spring in Israel. An automated time-height-resolved air mass source attribution method identifies the origin of the dust in the Sahara and the Arabian deserts. Fine-mode spherical particles contribute significantly to the observed aerosol mixture during all seasons. These particles originate mainly from the industrial region at the bay of Haifa.
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    Automated time–height-resolved air mass source attribution for profiling remote sensing applications
    (Katlenburg-Lindau : EGU, 2021) Radenz, Martin; Seifert, Patric; Baars, Holger; Floutsi, Athena Augusta; Yin, Zhenping; Bühl, Johannes
    Height-resolved air mass source attribution is crucial for the evaluation of profiling ground-based remote sensing observations, especially when using lidar (light detection and ranging) to investigate different aerosol types throughout the atmosphere. Lidar networks, such as EARLINET (European Aerosol Research Lidar Network) in the frame of ACTRIS (Aerosol, Clouds and Trace Gases), observe profiles of optical aerosol properties almost continuously, but usually, additional information is needed to support the characterization of the observed particles. This work presents an approach explaining how backward trajectories or particle positions from a dispersion model can be combined with geographical information (a land cover classification and manually defined areas) to obtain a continuous and vertically resolved estimate of an air mass source above a certain location. Ideally, such an estimate depends on as few as possible a priori information and auxiliary data. An automated framework for the computation of such an air mass source is presented, and two applications are described. First, the air mass source information is used for the interpretation of air mass sources for three case studies with lidar observations from Limassol (Cyprus), Punta Arenas (Chile) and ship-borne off Cabo Verde. Second, air mass source statistics are calculated for two multi-week campaigns to assess potential observation biases of lidar-based aerosol statistics. Such an automated approach is a valuable tool for the analysis of short-term campaigns but also for long-term data sets, for example, acquired by EARLINET.